Technical Program Manager

Description

The company is an applied AI engineering firm that designs and ships AI co-workers that plug into enterprise operations and produce measurable results for clients.

Most of the work runs on AWS. Senior UX and engineering talent work together to get AI into production quickly and keep it there.

Clients include firms in consumer products and retail, education, energy, financial services, healthcare, and manufacturing. Founded in 2009, the company has delivery centers in Canada, the United States, Eastern Europe, and Latin America. Its teams average 15+ years of experience.

This role owns large, multi-workstream programs from turning a client's business goals into a technical plan through launch and the value delivered afterward. You work between business and engineering, lead architecture and engineering discussions, shape technical direction with engineering leads, and keep distributed teams aimed at one outcome.

The largest engagements are enterprise AI, cloud, and agentic transformations with many teams, many stakeholders, and significant budgets. You keep these from fragmenting, aligning a client executive and an engineering lead on the same business result. When priorities clash or risk appears with little information and a tight deadline, you lay out the trade-off and drive the decision so production-ready AI holds at enterprise scale.

Work model: hybrid, with on-site days 3 days a week in NYC or Mountain View, CA.

Responsibilities

• Run end-to-end delivery of large ($10M+) AI, digital, and cloud programs, from strategy and roadmap through launch and realized business value.
• Split complex programs into workstreams you can deliver, each with clear ownership, sequencing, and dependencies.
• Drive schedules from design to launch across several concurrent Agile teams, keeping delivery and product managers on one integrated plan.
• Set program-level KPIs and governance, and use data to report health and guide decisions on scope, timeline, budget, and quality.
• Turn customer needs into technical requirements, and tie each one to the business outcome it supports.
• Lead engineering and architecture discussions with enough understanding of frontend, back-end, and product technology to steer team direction.
• Break hard technical problems into solutions the teams can execute.
• Contribute to technical documentation and set the documentation standards your programs follow.
• Own the AI Development Life Cycle (AIDLC) at program level, and set the standard senior delivery managers use to roll it out across workstreams.
• Define the program-wide done criteria for probabilistic and AI-driven features, including evaluation thresholds, human-in-the-loop checkpoints, and post-launch monitoring, and enforce them on every workstream.
• Work with AI engineering leads on model risk, data readiness, evaluation strategy, and observability for agentic work. Turn technical uncertainty into a plan and a risk register the client can act on.
• Define success for AI-assisted delivery by measuring quality, rework, review overhead, and velocity, not just passing tests. Keep status visible across complex AI pipelines.
• Decide when an agentic approach is the wrong tool, weighing context management, latency, infrastructure, and cost, and defend that call to the client.
• Use AI tools such as Claude every day for planning, specifications, reporting, and stakeholder communication, and show delivery leads how.
• Serve as the senior program partner to client executives, building trust through transparency, consistency, and clear communication.
• Spot bottlenecks early, manage escalations, and make trade-offs between business needs and technical constraints.
• Lead trade-off decisions with customers, stakeholders, and partner teams when priorities conflict, and manage escalations or misalignment whenever committed outcomes or quality are at risk.
• Report schedule, progress, and business impact to stakeholders and senior leaders so executives see value, not just status.
• Work with Client Partners to shape follow-on work and expansion opportunities that come out of the program.
• Lead and mentor Senior Delivery Managers and Delivery Managers with concrete feedback and stretch opportunities.
• Create clarity for teams in an environment where ambiguity and competing priorities are normal.
• Improve the firm's delivery practice, tools, and frameworks beyond your own programs.
• Assess staffing and capability gaps, and work with Client Partners and leadership on staffing needs and high-potential talent.
• Conduct executive interviews and act as a key voice in go/no-go hiring decisions across the firm.

Requirements

• 5+ years leading several Agile teams at once or at scale, including Scrum Masters and Product Owners.
• 5+ years leading and delivering enterprise-level IT engagements.
• Proven record leading $10M+ AI, digital, or cloud transformation programs from strategy through realized business value.
• Practical use of frameworks such as Well-Architected and the Cloud Adoption Framework to guide program decisions and solution governance.
• Credible grounding in architecture, frontend and back-end technology, and cloud-native design. You can break down complex problems and turn customer needs into technical and functional specifications mapped to business outcomes.
• Experience leading programs where AI/ML or agentic capability was central, including managing model risk, evaluation, and client expectations, and setting program-wide standards for evaluation, human-in-the-loop checkpoints, and monitoring.
• Daily use of AI tools (e.g., Claude) to improve planning, specifications, reporting, and documentation.
• Experience with delivery and engineering tools (e.g., Jira, Confluence, GitHub, Azure DevOps, CI/CD pipelines).
• Comfort working in ambiguity, with enough client credibility to bring growth conversations forward alongside Client Partners.
• You act without waiting for certainty, and you admit mistakes quickly.
• You stay curious as AI changes quickly, even with senior experience.
• You give direct, honest feedback and will have the hard conversation early.
• You care about detail and only put your name on work you would stand behind.
• You take ownership, keep commitments, and back your teammates when a decision costs something.
• You treat client businesses as your own and stay serious about the work without taking yourself too seriously.
• You stay effective when budget, timeline, or team is tight.
• You stay calm under pressure and raise hard trade-offs early.
• You enjoy working with people who push each other to do better work.
• Helpful extra: vertical depth in consumer products and retail, education, energy, financial services, healthcare, or manufacturing.
• Helpful extra: experience delivering agentic, AI co-worker, or applied-AI initiatives in enterprise settings.
• Helpful extra: thorough knowledge of AWS services, architectures, and best practices used to guide technical decisions and strategic planning.
• Helpful extra: you have owned end-to-end delivery of complex, multi-workstream agentic AI transformation programs.
• Helpful extra: earlier client-facing experience in engagement management, consulting, or account leadership that informs growth conversations.

Conditions

Hybrid role: on-site 3 days a week in NYC or Mountain View, CA.

Client travel of about 20% is required.

Base salary range is $180,000 USD - $215,000 USD. The range may change, and final pay may be above or below it.

Placement within the range depends on education, qualifications, certifications, experience, skills, seniority, location, performance, shift, travel requirements, sales or revenue metrics, any collective bargaining agreements, and business needs.

Benefits

• Paid time off.
• Medical, dental, and vision insurance.
• 401(k) for eligible employees.